project . 2018 - 2021 . On going

MUSKETEER

Machine learning to augment shared knowledge in federated privacy-preserving scenarios
Open Access mandate for Publications and Research DataOpen Access mandate for ... European Commission
  • Funder: European CommissionProject code: 824988 Call for proposal: H2020-ICT-2018-2
  • Funded under: H2020 | RIA Overall Budget: 4,380,350 EURFunder Contribution: 4,380,340 EUR
  • Status: On going
  • Start Date
    01 Dec 2018
    End Date
    30 Nov 2021
  • Detailed project information (CORDIS)
Description
The massive increase in data collected and stored worldwide calls for new ways to preserve privacy while still allowing data sharing among multiple data owners. Today, the lack of trusted and secure environments for data sharing inhibits data economy while legality, privacy, trustworthiness, data value and confidentiality hamper the free flow of data. By the end of the project, MUSKETEER aims to create a validated, federated, privacy-preserving machine learning platform tested on industrial data that is inter-operable, scalable and efficient enough to be deployed in real use cases. MUSKETEER aims to alleviate data sharing barriers by providing secure, scalable a...
Description
The massive increase in data collected and stored worldwide calls for new ways to preserve privacy while still allowing data sharing among multiple data owners. Today, the lack of trusted and secure environments for data sharing inhibits data economy while legality, privacy, trustworthiness, data value and confidentiality hamper the free flow of data. By the end of the project, MUSKETEER aims to create a validated, federated, privacy-preserving machine learning platform tested on industrial data that is inter-operable, scalable and efficient enough to be deployed in real use cases. MUSKETEER aims to alleviate data sharing barriers by providing secure, scalable a...
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